As generative AI becomes deeply woven into enterprise workflows, the need for ethical, scalable, and trustworthy data practices has never been greater. This course dives into two foundational pillars of modern AI strategy: Traceable Data Lineage and Responsible AI Governance.
Data Lineage & Ethical Frameworks for Responsible AI
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Data Lineage & Ethical Frameworks for Responsible AI
This course is part of Modern Data Strategy for Enterprise Generative AI Specialization
Instructors: David Drummond
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
8 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Explain the role of traceable data lineage in AI reliability.
Apply governance frameworks to manage ethical and regulatory risks.
Tag and trace AI-generated content using modern tools.
Design scalable governance strategies for enterprise AI applications.
Skills you'll gain
Details to know
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Recently updated!
September 2025
Assessments
9 assignments
Taught in English
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This course is part of the Modern Data Strategy for Enterprise Generative AI Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course
As AI-generated content and data-driven systems become central to digital ecosystems, organizations must adopt strong governance practices to ensure transparency, accountability, and trust. This module introduces the need for data governance, explores its core concepts and frameworks, and explains how provenance technologies like C2PA help verify digital content authenticity. You'll learn how to tag AI-generated content, detect misinformation, and apply ethical AI principles in real-time environments. The module also covers tools like DuckLake, use cases in misinformation detection, and global perspectives such as the World Economic Forum’s AI Governance Framework—equipping you to build responsible, resilient, and trustworthy AI systems.
What's included
8 videos3 readings3 assignments1 plugin
In this module, you’ll dive into the world of data pipelines—the invisible engines powering modern analytics and AI. You’ll explore why they matter, how to build them with governance in mind, and what it takes to keep them running smoothly. You’ll get hands-on with demos that show how to visualize and monitor data flows, and discover how data lineage helps track where data comes from, how it changes, and where it goes. By the end, you’ll understand how to design smarter, more trustworthy pipelines that support transparency, compliance, and real-time decision-making.
What's included
6 videos1 reading3 assignments2 ungraded labs1 plugin
In this module, you’ll explore how to build AI systems that are not only powerful but also principled. From understanding the core principles of responsible AI to designing ethics-by-design workflows, you’ll learn how to embed trust and accountability into every stage of the AI lifecycle. Discover how governance automation, security frameworks, and advanced governance patterns can elevate your data strategy, while staying ahead of future trends in AI and compliance. Whether you're shaping policy or building systems, this module equips you to lead with integrity in the age of intelligent technology.
What's included
10 videos3 assignments1 plugin
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Frequently asked questions
This course provides practical frameworks and techniques for implementing ethical, traceable, and compliant data practices for AI systems. It's important because organizations face increasing regulatory scrutiny and public expectations regarding AI transparency and ethics.
This course is designed for professionals who need to ensure AI systems meet ethical standards and regulatory requirements while maintaining data traceability and governance.
You'll be able to design governance frameworks for AI systems, implement data lineage tracking, create ethics-by-design workflows, and establish content authenticity verification systems. These skills enable you to build responsible AI systems that maintain trust and compliance.
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